Neural network models offer a totally new approach to intelligent information processing that is robust, fault tolerant, and can be extremely fast. Such neural networks are discussed, for example, in A. P. Thakoor et al, "Binary Synaptic Connections Based on Memory Switching in a-Si:H", Neural Networks for Computing, J. S. Denker, Ed., American Institute of Physics Conference Proceedings #151, Snowbird, Utah, pp. 426-431 (1986).
The aforementioned features originate directly from the massive interconnectivity of neurons (the decision-making elements) in the brain and its ability to store information in a distributed manner as a large number of synaptic interconnects of varying strengths. Hardware implementations of neural network concepts, therefore, are attracting considerable attention. Such artificial neural networks are expected, for example, to function as high speed, content addressable, associative memories in large knowledge bases for artificial intelligence applications and robotics or to perform complex computational tasks such as combinatorial optimization for autonomous systems.
In particular, electronic implementation of an associative memory based on neural network models requires large arrays of extremely simple, binary connection elements or synaptic interconnects. Information is essentially stored in the binary states of the interconnects. Non-volatile storage of information therefore can take place at the time of fabrication of the synaptic array by making the resistive state of the desired interconnect "ON" or "OFF". Alternatively, significantly more useful memory systems can be built if programmable, binary resistive thin film devices (non-volatile microswitches) are used as synaptic interconnects.
Non-volatile, associative electronic memories based upon neural network models, with dense synaptic interconnection arrays in thin-film form, have recently been developed using hydrogenated amorphous silicon (a-Si:H). Similarly, using conventional photolithography, manganese dioxide based synapses have also been fabricated. Irreversible memory switching in hydrogenated amorphous silicon (OFF--&gt;ON) and manganese dioxide (ON--&gt;OFF) makes them ideally suited only for use as programmable, binary, weak synaptic connections in associative programmable read-only memories (PROMS) based on neural networks models. For many applications in computing and memory operations, it is also desirable to obtain the equivalents of erasable PROMs (EPROMs), such that the switching state can be reversed when desired (ON--&gt;OFF--&gt;ON etc.). A further desireable feature would allow control over the non-volatile resistance value so as to be able to predetermine a desired ON-state resistance value. Application Ser. No. 07/133,897, filed Dec. 16, 1987, and assigned to the same assignee as the present application discloses an EPROM having these characteristics, adapted especially for use in synaptic memory matrices. That system employs a resistive switching element that acts by transfer of ions from one layer to another. In some cases, it would be desirable to perform such switching in a faster manner than is possible with ion transfer, and to employ a switch with fewer layers--thus simpler and therefore cheaper to fabricate.